class_docstr: A compact implementation of agents for Atari 100k.
docstr: Resets the agent state by filling it with zeros.
docstr_tok: ["Resets","the","agent","state","by","filling","it","with","zeros","."]
code: def reset_all(self, new_obs):
      """Resets the agent state by filling it with zeros."""
      n_envs = new_obs.shape[0]
      self.state = onp.zeros((n_envs, *self.state_shape))
      self._record_observation(new_obs)
  
imports: import copy
  import functools
  from absl import logging
  from dopamine.jax import networks
  from dopamine.jax.agents.full_rainbow import full_rainbow_agent
  import gin
  import jax
  import jax.numpy
  import numpy
  import tensorflow
label_desc: Use image node_id 6 for calling the Atari100kRainbowAgent obj's underlying member method code with example usage: obj.reset_all(new_obs) without return types